1. Field of the Invention
This invention is directed to a computer modeling application for scheduling transportation, an apparatus comprising the same and a method for scheduling transportation using the same. More particularly, the invention is directed to a computer modeling application for finding the optimal solution to maximize total net margin for the assignment of transportation vehicles (especially vessels) in an available fleet to perform a set of voyages to be initiated during a planning period for transporting cargo comprising one or more bulk products, as well as an apparatus and method employing the same.
2. Description of Related Art
Marine transportation is an important aspect for many industries including the oil and gas industry. Marine transportation is an economically attractive means to vessel bulk product (e.g., bulk liquids such as crude oil) over long distances. Accordingly, large volumes of bulk product are moved daily across the oceans and seas by a variety of vessels between source and destination locations. Destination ports (e.g., refinery sites) may be geographically spread around the world and are often far from the source of the bulk product (e.g., crude oil) needed. Because distances are large, transportation costs are significant. In addition, the business environment of marine transportation is complex and dynamic in that the number of shipping options is large and varies at any given time depending upon the amount of product that needs to be transported, temporal restrictions for the transport, the physical limitations of available vessels and relevant ports, vessel contractual terms and conditions, etc. Accordingly, marine transportation scheduling decisions are complex and dynamic.
The conventional commercial practice for making vessel scheduling decisions is to perform a manual analysis of available options with the assistance of spreadsheets. An experienced staff will use spreadsheets to calculate voyage constraints, estimate economic trade-offs, project voyage events forward in time and evaluate potential decisions. The staff may also apply heuristics, business rules and guidelines and intuition to develop an acceptable cargo transportation (i.e., lifting) program. The process is time consuming, incomplete, and there is no realistic way to know whether the lifting program chosen is, or is not, optimal. Given the typically large number of feasible vessel/voyage assignments, it is very difficult, if not impossible, to determine an optimal lifting program by manually considering one voyage (or one vessel) at a time. There are interactions between the various assignment decisions (e.g., if a given vessel is assigned to a given voyage, then the vessel is no longer available for one or more alternate concurrent voyages). The number of interactions, the number of possible decisions, and the number of significant factors are far too complex to be fully optimized manually (particularly in an acceptable time frame for making business decisions) even by an experienced scheduler. The problem is further complicated as one attempts to account for sequences of one or more voyages which can be assigned to a given vessel. In addition, once a manually derived schedule has been completed, it is impractical to frequently repeat the scheduling process to reflect changes in the business environment which can occur daily.
TurboRouter® is a tool recently developed by the Norwegian Marine Technology Research Institute, MARINTEK Logistics, and it performs vessel routing and scheduling calculations. However, the tool is based on a heuristic approach rather than an optimization approach. In addition, the purpose of the tool is to allow a commercial shipping company, as opposed to a chartering party, to maximize the revenue obtained by shipping optional cargo in addition to contract cargos that must be shipped.
There have been numerous publications in the field of ship routing and scheduling. One survey article is Ship routing and scheduling: status and perspectives, Transportation Science, 38(1): 1-18, M. Christiansen, K. Fagerholt, and D. Ronen (2004). One overview article is Marine Transportation, Handbooks in Operations Research and Management Science Transportation, M. Christiansen, K. Fagerholt, B. Nygreen, D. Ronen, edited by C. Barnhart and G. Laporte (2005).
One publication of note is Scheduling Ocean Transportation of Crude Oil, Management Science, G. G. Brown, G. W. Graves, D. Ronen, 33(3): 335-346 (1987). This paper addresses a crude oil marine transportation problem. However, the modeling problem described therein includes the following assumptions/simplifications: (1) each cargo (i.e., crude oil to be shipped) moves between a single loading port and a single discharging port; (2) the cargo shipped must always be a full ship load (i.e., the cargo must be of a fixed size); and (3) each vessel is the same size. In addition, the objective function of the model is to minimize cost as opposed to net margin (i.e., revenue or value minus costs).
Another publication of note is Fleet management models and algorithms for an oil tanker routing and scheduling problem, H. D. Sherali, S. M. Al-Yakoob, M. M. Hassan, IIE Trans. 31: 395-406 (1999). This paper also addresses a crude oil marine transportation modeling problem. Again, the modeling problem characteristics are such that each voyage must consist of a single loading port and a single discharging port and each cargo must be a full vessel load. In addition, the objective is to minimize cost as opposed to net margin. The problem addressed in this paper is different from the preceding paper in that the problem in that the ships do not have to be the same size and there is an explicit treatment of vessel compartments.
None of the work above provides a marine transportation lifting program that represents general vessel scheduling business problem characteristics and/or constraints. For example, in a typical vessel scheduling problem, each voyage consists of multiple loading ports and multiple discharging ports, the cargos lifted may vary in weight and/or volume, and the vessels available to perform the voyage may vary in a number of ways including, but not limited to, capacity and charter type (e.g., spot vessels and term vessels).
Further, none of the work above provides a marine transportation lifting program that optimally maximizes the total net margin for a chartering party as opposed to merely minimizing cost. A cost minimization approach is inadequate as is does not correctly represent the economic impact of vessel assignment decisions, does not properly reflect the trade-offs between the use of term and spot vessels and does not value long and short voyages on a consistent basis.
Accordingly, as set forth below, a novel and creative computer application has been developed for making optimal transportation scheduling decisions. The application is able to determine the optimal solution to maximize total net margin for the assignment of vehicles (e.g., vessels) in an available fleet to perform a set of voyages reflecting common scheduling problem characteristics and constraints.
The detailed drawings are provided for the purposes of illustration only. The particular data set forth in the various illustrative spreadsheets is hypothetical but representative data for a hypothetical but representative scheduling problem. Accordingly, the results derived there from are similarly hypothetical but representative.